dc.contributor.author
Hu, Jiun‐Yiing
dc.contributor.author
Kirilina, Evgeniya
dc.contributor.author
Nierhaus, Till
dc.contributor.author
Ovadia‐Caro, Smadar
dc.contributor.author
Livne, Michelle
dc.contributor.author
Villringer, Kersten
dc.contributor.author
Margulies, Daniel
dc.contributor.author
Fiebach, Jochen B.
dc.contributor.author
Villringer, Arno
dc.contributor.author
Khalil, Ahmed A.
dc.date.accessioned
2022-11-04T15:44:24Z
dc.date.available
2022-11-04T15:44:24Z
dc.identifier.uri
https://refubium.fu-berlin.de/handle/fub188/36719
dc.identifier.uri
http://dx.doi.org/10.17169/refubium-36432
dc.description.abstract
Individualized treatment of acute stroke depends on the timely detection of ischemia and potentially salvageable tissue in the brain. Using functional MRI (fMRI), it is possible to characterize cerebral blood flow from blood-oxygen-level-dependent (BOLD) signals without the administration of exogenous contrast agents. In this study, we applied spatial independent component analysis to resting-state fMRI data of 37 stroke patients scanned within 24 hr of symptom onset, 17 of whom received follow-up scans the next day. Our analysis revealed "Hypoperfusion spatially-Independent Components" (HICs) whose spatial patterns of BOLD signal resembled regions of delayed perfusion depicted by dynamic susceptibility contrast MRI. These HICs were detected even in the presence of excessive patient motion, and disappeared following successful tissue reperfusion. The unique spatial and temporal features of HICs allowed them to be distinguished with high accuracy from other components in a user-independent manner (area under the curve = 0.93, balanced accuracy = 0.90, sensitivity = 1.00, and specificity = 0.85). Our study therefore presents a new, noninvasive method for assessing blood flow in acute stroke that minimizes interpretative subjectivity and is robust to severe patient motion.
en
dc.rights.uri
https://creativecommons.org/licenses/by/4.0/
dc.subject
blood oxygenation level dependent signal
en
dc.subject
resting-state functional magnetic resonance imaging
en
dc.subject
spatial independent component analysis
en
dc.subject.ddc
600 Technik, Medizin, angewandte Wissenschaften::610 Medizin und Gesundheit::610 Medizin und Gesundheit
dc.title
A novel approach for assessing hypoperfusion in stroke using spatial independent component analysis of resting‐state fMRI
dc.type
Wissenschaftlicher Artikel
dcterms.bibliographicCitation.doi
10.1002/hbm.25610
dcterms.bibliographicCitation.journaltitle
Human Brain Mapping
dcterms.bibliographicCitation.number
16
dcterms.bibliographicCitation.originalpublishername
Wiley
dcterms.bibliographicCitation.pagestart
5204
dcterms.bibliographicCitation.pageend
5216
dcterms.bibliographicCitation.volume
42
refubium.affiliation
Charité - Universitätsmedizin Berlin
refubium.funding
DEAL Wiley
refubium.resourceType.isindependentpub
no
dcterms.accessRights.openaire
open access
dcterms.bibliographicCitation.pmid
34323339
dcterms.isPartOf.issn
1065-9471
dcterms.isPartOf.eissn
1097-0193